33 results on '"Saeedi, Farhad"'
Search Results
2. Clinical utility of lipid ratios as potential predictors of metabolic syndrome among the elderly population: Birjand Longitudinal Aging Study (BLAS)
- Author
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Saeedi, Farhad, Baqeri, Elnaz, Bidokhti, Ali, Moodi, Mitra, Sharifi, Farshad, and Riahi, Seyed Mohammad
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- 2023
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3. Correction to: Associations of emotional social support, depressive symptoms, chronic stress, and anxiety with hard cardiovascular disease events in the United States: the multi-ethnic study of atherosclerosis (MESA)
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Riahi, Seyed Mohammad, Yousefi, Ahmad, Saeedi, Farhad, and Martin, Seth Shay
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- 2023
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4. Associations of emotional social support, depressive symptoms, chronic stress, and anxiety with hard cardiovascular disease events in the United States: the multi-ethnic study of atherosclerosis (MESA)
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Riahi, Seyed Mohammad, Yousefi, Ahmad, Saeedi, Farhad, and Martin, Seth Shay
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- 2023
- Full Text
- View/download PDF
5. Comparison of decision tree with common machine learning models for prediction of biguanide and sulfonylurea poisoning in the United States: an analysis of the National Poison Data System
- Author
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Mehrpour, Omid, Saeedi, Farhad, Nakhaee, Samaneh, Tavakkoli Khomeini, Farbod, Hadianfar, Ali, Amirabadizadeh, Alireza, and Hoyte, Christopher
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- 2023
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6. Utility of artificial intelligence to identify antihyperglycemic agents poisoning in the USA: introducing a practical web application using National Poison Data System (NPDS)
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Mehrpour, Omid, Nakhaee, Samaneh, Saeedi, Farhad, Valizade, Bahare, Lotfi, Erfan, and Nawaz, Malik Hamza
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- 2023
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7. Clinical and pharmacokinetics overview of intranasal administration of fentanyl
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Nakhaee, Samaneh, Saeedi, Farhad, and Mehrpour, Omid
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- 2023
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8. Population-level risks of alcohol consumption by amount, geography, age, sex, and year: a systematic analysis for the Global Burden of Disease Study 2020
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Bryazka, Dana, Reitsma, Marissa B, Griswold, Max G, Abate, Kalkidan Hassen, Abbafati, Cristiana, Abbasi-Kangevari, Mohsen, Abbasi-Kangevari, Zeinab, Abdoli, Amir, Abdollahi, Mohammad, Abdullah, Abu Yousuf Md, Abhilash, E S, Abu-Gharbieh, Eman, Acuna, Juan Manuel, Addolorato, Giovanni, Adebayo, Oladimeji M, Adekanmbi, Victor, Adhikari, Kishor, Adhikari, Sangeet, Adnani, Qorinah Estiningtyas Sakilah, Afzal, Saira, Agegnehu, Wubetu Yimam, Aggarwal, Manik, Ahinkorah, Bright Opoku, Ahmad, Araz Ramazan, Ahmad, Sajjad, Ahmad, Tauseef, Ahmadi, Ali, Ahmadi, Sepideh, Ahmed, Haroon, Ahmed Rashid, Tarik, Akunna, Chisom Joyqueenet, Al Hamad, Hanadi, Alam, Md Zakiul, Alem, Dejene Tsegaye, Alene, Kefyalew Addis, Alimohamadi, Yousef, Alizadeh, Atiyeh, Allel, Kasim, Alonso, Jordi, Alvand, Saba, Alvis-Guzman, Nelson, Amare, Firehiwot, Ameyaw, Edward Kwabena, Amiri, Sohrab, Ancuceanu, Robert, Anderson, Jason A, Andrei, Catalina Liliana, Andrei, Tudorel, Arabloo, Jalal, Arshad, Muhammad, Artamonov, Anton A, Aryan, Zahra, Asaad, Malke, Asemahagn, Mulusew A, Astell-Burt, Thomas, Athari, Seyyed Shamsadin, Atnafu, Desta Debalkie, Atorkey, Prince, Atreya, Alok, Ausloos, Floriane, Ausloos, Marcel, Ayano, Getinet, Ayanore, Martin Amogre ayanore, Ayinde, Olatunde O, Ayuso-Mateos, Jose L, Azadnajafabad, Sina, Azanaw, Melkalem Mamuye, Azangou-Khyavy, Mohammadreza, Azari Jafari, Amirhossein, Azzam, Ahmed Y, Badiye, Ashish D, Bagheri, Nasser, Bagherieh, Sara, Bairwa, Mohan, Bakkannavar, Shankar M, Bakshi, Ravleen Kaur, Balchut/Bilchut, Awraris Hailu, Bärnighausen, Till Winfried, Barra, Fabio, Barrow, Amadou, Baskaran, Pritish, Belo, Luis, Bennett, Derrick A, Benseñor, Isabela M, Bhagavathula, Akshaya Srikanth, Bhala, Neeraj, Bhalla, Ashish, Bhardwaj, Nikha, Bhardwaj, Pankaj, Bhaskar, Sonu, Bhattacharyya, Krittika, Bhojaraja, Vijayalakshmi S, Bintoro, Bagas Suryo, Blokhina, Elena A Elena, Bodicha, Belay Boda Abule, Boloor, Archith, Bosetti, Cristina, Braithwaite, Dejana, Brenner, Hermann, Briko, Nikolay Ivanovich, Brunoni, Andre R, Butt, Zahid A, Cao, Chao, Cao, Yin, Cárdenas, Rosario, Carvalho, Andre F, Carvalho, Márcia, Castaldelli-Maia, Joao Mauricio, Castelpietra, Giulio, Castro-de-Araujo, Luis F S, Cattaruzza, Maria Sofia, Chakraborty, Promit Ananyo, Charan, Jaykaran, Chattu, Vijay Kumar, Chaurasia, Akhilanand, Cherbuin, Nicolas, Chu, Dinh-Toi, Chudal, Nandita, Chung, Sheng-Chia, Churko, Chuchu, Ciobanu, Liliana G, Cirillo, Massimo, Claro, Rafael M, Costanzo, Simona, Cowden, Richard G, Criqui, Michael H, Cruz-Martins, Natália, Culbreth, Garland T, Dachew, Berihun Assefa, Dadras, Omid, Dai, Xiaochen, Damiani, Giovanni, Dandona, Lalit, Dandona, Rakhi, Daniel, Beniam Darge, Danielewicz, Anna, Darega Gela, Jiregna, Davletov, Kairat, de Araujo, Jacyra Azevedo Paiva, de Sá-Junior, Antonio Reis, Debela, Sisay Abebe, Dehghan, Azizallah, Demetriades, Andreas K, Derbew Molla, Meseret, Desai, Rupak, Desta, Abebaw Alemayehu, Dias da Silva, Diana, Diaz, Daniel, Digesa, Lankamo Ena, Diress, Mengistie, Dodangeh, Milad, Dongarwar, Deepa, Dorostkar, Fariba, Dsouza, Haneil Larson, Duko, Bereket, Duncan, Bruce B, Edvardsson, Kristina, Ekholuenetale, Michael, Elgar, Frank J, Elhadi, Muhammed, Elmonem, Mohamed A, Endries, Aman Yesuf, Eskandarieh, Sharareh, Etemadimanesh, Azin, Fagbamigbe, Adeniyi Francis, Fakhradiyev, Ildar Ravisovich, Farahmand, Fatemeh, Farinha, Carla Sofia e Sá, Faro, Andre, Farzadfar, Farshad, Fatehizadeh, Ali, Fauk, Nelsensius Klau, Feigin, Valery L, Feldman, Rachel, Feng, Xiaoqi, Fentaw, Zinabu, Ferrero, Simone, Ferro Desideri, Lorenzo, Filip, Irina, Fischer, Florian, Francis, Joel Msafiri, Franklin, Richard Charles, Gaal, Peter Andras, Gad, Mohamed M, Gallus, Silvano, Galvano, Fabio, Ganesan, Balasankar, Garg, Tushar, Gebrehiwot, Mesfin Gebrehiwot Damtew, Gebremeskel, Teferi Gebru, Gebremichael, Mathewos Alemu, Gemechu, Tadele Regasa, Getacher, Lemma, Getachew, Motuma Erena, Getachew Obsa, Abera, Getie, Asmare, Ghaderi, Amir, Ghafourifard, Mansour, Ghajar, Alireza, Ghamari, Seyyed-Hadi, Ghandour, Lilian A, Ghasemi Nour, Mohammad, Ghashghaee, Ahmad, Ghozy, Sherief, Glozah, Franklin N, Glushkova, Ekaterina Vladimirovna, Godos, Justyna, Goel, Amit, Goharinezhad, Salime, Golechha, Mahaveer, Goleij, Pouya, Golitaleb, Mohamad, Greaves, Felix, Grivna, Michal, Grosso, Giuseppe, Gudayu, Temesgen Worku, Gupta, Bhawna, Gupta, Rajeev, Gupta, Sapna, Gupta, Veer Bala, Gupta, Vivek Kumar, Hafezi-Nejad, Nima, Haj-Mirzaian, Arvin, Hall, Brian J, Halwani, Rabih, Handiso, Tiilahun Beyene, Hankey, Graeme J, Hariri, Sanam, Haro, Josep Maria, Hasaballah, Ahmed I, Hassanian-Moghaddam, Hossein, Hay, Simon I, Hayat, Khezar, Heidari, Golnaz, Heidari, Mohammad, Hendrie, Delia, Herteliu, Claudiu, Heyi, Demisu Zenbaba, Hezam, Kamal, Hlongwa, Mbuzeleni Mbuzeleni, Holla, Ramesh, Hossain, Md Mahbub, Hossain, Sahadat, Hosseini, Seyed Kianoosh, hosseinzadeh, Mehdi, Hostiuc, Mihaela, Hostiuc, Sorin, Hu, Guoqing, Huang, Junjie, Hussain, Salman, Ibitoye, Segun Emmanuel, Ilic, Irena M, Ilic, Milena D, Immurana, Mustapha, Irham, Lalu Muhammad, Islam, M Mofizul, Islam, Rakibul M, Islam, Sheikh Mohammed Shariful, Iso, Hiroyasu, Itumalla, Ramaiah, Iwagami, Masao, Jabbarinejad, Roxana, Jacob, Louis, Jakovljevic, Mihajlo, Jamalpoor, Zahra, Jamshidi, Elham, Jayapal, Sathish Kumar, Jayarajah, Umesh Umesh, Jayawardena, Ranil, Jebai, Rime, Jeddi, Seyed Ali, Jema, Alelign Tasew, Jha, Ravi Prakash, Jindal, Har Ashish, Jonas, Jost B, Joo, Tamas, Joseph, Nitin, Joukar, Farahnaz, Jozwiak, Jacek Jerzy, Jürisson, Mikk, Kabir, Ali, Kabthymer, Robel Hussen, Kamble, Bhushan Dattatray, Kandel, Himal, Kanno, Girum Gebremeskel, Kapoor, Neeti, Karaye, Ibraheem M, Karimi, Salah Eddin, Kassa, Bekalu Getnet, Kaur, Rimple Jeet, Kayode, Gbenga A, Keykhaei, Mohammad, Khajuria, Himanshu, Khalilov, Rovshan, Khan, Imteyaz A, Khan, Moien AB, Kim, Hanna, Kim, Jihee, Kim, Min Seo, Kimokoti, Ruth W, Kivimäki, Mika, Klymchuk, Vitalii, Knudsen, Ann Kristin Skrindo, Kolahi, Ali-Asghar, Korshunov, Vladimir Andreevich, Koyanagi, Ai, Krishan, Kewal, Krishnamoorthy, Yuvaraj, Kumar, G Anil, Kumar, Narinder, Kumar, Nithin, Lacey, Ben, Lallukka, Tea, Lasrado, Savita, Lau, Jerrald, Lee, Sang-woong, Lee, Wei-Chen, Lee, Yo Han, Lim, Lee-Ling, Lim, Stephen S, Lobo, Stany W, Lopukhov, Platon D, Lorkowski, Stefan, Lozano, Rafael, Lucchetti, Giancarlo, Madadizadeh, Farzan, Madureira-Carvalho, Áurea M, Mahjoub, Soleiman, Mahmoodpoor, Ata, Mahumud, Rashidul Alam, Makki, Alaa, Malekpour, Mohammad-Reza, Manjunatha, Narayana, Mansouri, Borhan, Mansournia, Mohammad Ali, Martinez-Raga, Jose, Martinez-Villa, Francisco A, Matzopoulos, Richard, Maulik, Pallab K, Mayeli, Mahsa, McGrath, John J, Meena, Jitendra Kumar, Mehrabi Nasab, Entezar, Menezes, Ritesh G, Mensink, Gert B M, Mentis, Alexios-Fotios A, Meretoja, Atte, Merga, Bedasa Taye, Mestrovic, Tomislav, Miao Jonasson, Junmei, Miazgowski, Bartosz, Micheletti Gomide Nogueira de Sá, Ana Carolina, Miller, Ted R, Mini, GK, Mirica, Andreea, Mirijello, Antonio, Mirmoeeni, Seyyedmohammadsadeq, Mirrakhimov, Erkin M, Misra, Sanjeev, Moazen, Babak, Mobarakabadi, Maryam, Moccia, Marcello, Mohammad, Yousef, Mohammadi, Esmaeil, Mohammadian-Hafshejani, Abdollah, Mohammed, Teroj Abdulrahman, Moka, Nagabhishek, Mokdad, Ali H, Momtazmanesh, Sara, Moradi, Yousef, Mostafavi, Ebrahim, Mubarik, Sumaira, Mullany, Erin C, Mulugeta, Beemnet Tekabe, Murillo-Zamora, Efrén, Murray, Christopher J L, Mwita, Julius C, Naghavi, Mohsen, Naimzada, Mukhammad David, Nangia, Vinay, Nayak, Biswa Prakash, Negoi, Ionut, Negoi, Ruxandra Irina, Nejadghaderi, Seyed Aria, Nepal, Samata, Neupane, Sudan Prasad Prasad, Neupane Kandel, Sandhya, Nigatu, Yeshambel T, Nowroozi, Ali, Nuruzzaman, Khan M, Nzoputam, Chimezie Igwegbe, Obamiro, Kehinde O, Ogbo, Felix Akpojene, Oguntade, Ayodipupo Sikiru, Okati-Aliabad, Hassan, Olakunde, Babayemi Oluwaseun, Oliveira, Gláucia Maria Moraes, Omar Bali, Ahmed, Omer, Emad, Ortega-Altamirano, Doris V, Otoiu, Adrian, Otstavnov, Stanislav S, Oumer, Bilcha, P A, Mahesh, Padron-Monedero, Alicia, Palladino, Raffaele, Pana, Adrian, Panda-Jonas, Songhomitra, Pandey, Anamika, Pandey, Ashok, Pardhan, Shahina, Parekh, Tarang, Park, Eun-Kee, Parry, Charles D H, Pashazadeh Kan, Fatemeh, Patel, Jay, Pati, Siddhartha, Patton, George C, Paudel, Uttam, Pawar, Shrikant, Peden, Amy E, Petcu, Ionela-Roxana, Phillips, Michael R, Pinheiro, Marina, Plotnikov, Evgenii, Pradhan, Pranil Man Singh, Prashant, Akila, Quan, Jianchao, Radfar, Amir, Rafiei, Alireza, Raghav, Pankaja Raghav, Rahimi-Movaghar, Vafa, Rahman, Azizur, Rahman, Md Mosfequr, Rahman, Mosiur, Rahmani, Amir Masoud, Rahmani, Shayan, Ranabhat, Chhabi Lal, Ranasinghe, Priyanga, Rao, Chythra R, Rasali, Drona Prakash, Rashidi, Mohammad-Mahdi, Ratan, Zubair Ahmed, Rawaf, David Laith, Rawaf, Salman, Rawal, Lal, Renzaho, Andre M N, Rezaei, Negar, Rezaei, Saeid, Rezaeian, Mohsen, Riahi, Seyed Mohammad, Romero-Rodríguez, Esperanza, Roth, Gregory A, Rwegerera, Godfrey M, Saddik, Basema, Sadeghi, Erfan, Sadeghian, Reihaneh, Saeed, Umar, Saeedi, Farhad, Sagar, Rajesh, Sahebkar, Amirhossein, Sahoo, Harihar, Sahraian, Mohammad Ali, Saif-Ur-Rahman, KM, Salahi, Sarvenaz, Salimzadeh, Hamideh, Samy, Abdallah M, Sanmarchi, Francesco, Santric-Milicevic, Milena M, Sarikhani, Yaser, Sathian, Brijesh, Saya, Ganesh Kumar, Sayyah, Mehdi, Schmidt, Maria Inês, Schutte, Aletta Elisabeth, Schwarzinger, Michaël, Schwebel, David C, Seidu, Abdul-Aziz, Senthil Kumar, Nachimuthu, SeyedAlinaghi, SeyedAhmad, Seylani, Allen, Sha, Feng, Shahin, Sarvenaz, Shahraki-Sanavi, Fariba, Shahrokhi, Shayan, Shaikh, Masood Ali, Shaker, Elaheh, Shakhmardanov, Murad Ziyaudinovich, Shams-Beyranvand, Mehran, Sheikhbahaei, Sara, Sheikhi, Rahim Ali, Shetty, Adithi, Shetty, Jeevan K, Shiferaw, Damtew Solomon, Shigematsu, Mika, Shiri, Rahman, Shirkoohi, Reza, Shivakumar, K M, Shivarov, Velizar, Shobeiri, Parnian, Shrestha, Roman, Sidemo, Negussie Boti, Sigfusdottir, Inga Dora, Silva, Diego Augusto Santos, Silva, Natacha Torres da, Singh, Jasvinder A, Singh, Surjit, Skryabin, Valentin Yurievich, Skryabina, Anna Aleksandrovna, Sleet, David A, Solmi, Marco, SOLOMON, YONATAN, Song, Suhang, Song, Yimeng, Sorensen, Reed J D, Soshnikov, Sergey, Soyiri, Ireneous N, Stein, Dan J, Subba, Sonu Hangma, Szócska, Miklós, Tabarés-Seisdedos, Rafael, Tabuchi, Takahiro, Taheri, Majid, Tan, Ker-Kan, Tareke, Minale, Tarkang, Elvis Enowbeyang, Temesgen, Gebremaryam, Temesgen, Worku Animaw, Temsah, Mohamad-Hani, Thankappan, Kavumpurathu Raman, Thapar, Rekha, Thomas, Nikhil Kenny, Tiruneh, Chalachew, Todorovic, Jovana, Torrado, Marco, Touvier, Mathilde, Tovani-Palone, Marcos Roberto, Tran, Mai Thi Ngoc, Trias-Llimós, Sergi, Tripathy, Jaya Prasad, Vakilian, Alireza, Valizadeh, Rohollah, Varmaghani, Mehdi, Varthya, Shoban Babu, Vasankari, Tommi Juhani, Vos, Theo, Wagaye, Birhanu, Waheed, Yasir, Walde, Mandaras Tariku, Wang, Cong, Wang, Yanzhong, Wang, Yuan-Pang, Westerman, Ronny, Wickramasinghe, Nuwan Darshana, Wubetu, Abate Dargie, Xu, Suowen, Yamagishi, Kazumasa, Yang, Lin, Yesera, Gesila Endashaw E, Yigit, Arzu, Yiğit, Vahit, Yimaw, Ayenew Engida Ayenew Engida, Yon, Dong Keon, Yonemoto, Naohiro, Yu, Chuanhua, Zadey, Siddhesh, Zahir, Mazyar, Zare, Iman, Zastrozhin, Mikhail Sergeevich, Zastrozhina, Anasthasia, Zhang, Zhi-Jiang, Zhong, Chenwen, Zmaili, Mohammad, Zuniga, Yves Miel H, and Gakidou, Emmanuela
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- 2022
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9. Distinguishing characteristics of exposure to biguanide and sulfonylurea anti-diabetic medications in the United States
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Mehrpour, Omid, Saeedi, Farhad, Hoyte, Christopher, Hadianfar, Ali, Nakhaee, Samaneh, and Brent, Jeffrey
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- 2022
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10. Correction: Utility of support vector machine and decision tree to identify the prognosis of metformin poisoning in the United States: analysis of National Poisoning Data System
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Mehrpour, Omid, Saeedi, Farhad, Hoyte, Christopher, Goss, Foster, and Shirazi, Farshad M.
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- 2022
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11. Utility of support vector machine and decision tree to identify the prognosis of metformin poisoning in the United States: analysis of National Poisoning Data System
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Mehrpour, Omid, Saeedi, Farhad, Hoyte, Christopher, Goss, Foster, and Shirazi, Farshad M.
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- 2022
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12. Outcome prediction of methadone poisoning in the United States: implications of machine learning in the National Poison Data System (NPDS).
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Mehrpour, Omid, Saeedi, Farhad, Vohra, Varun, and Hoyte, Christopher
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OPIOID receptors , *POISONS , *RANDOM forest algorithms , *DATABASES , *METHADONE hydrochloride - Abstract
Methadone is an opioid receptor agonist with a high potential for abuse. The current study aimed to compare different machine learning models to predict the outcomes following methadone poisoning. This six-year retrospective longitudinal study utilizes National Poison Data System (NPDS) data. The severity of outcomes was derived from the NPDS Coding Manual. Our database was divided into training (70%) and test (30%) sets. We used a light gradient boosting machine (LGBM), extreme gradient boosting (XGBoost), random forest (RF), and logistic regression (LR) to predict the outcomes of methadone poisoning. A total of 3847 patients with methadone exposures were included. Our results demonstrated that machine learning models conferred high accuracy and reliability in determining the outcomes of methadone poisoning cases. The performance evaluation showed all models had high accuracy, precision, specificity, recall, and F1-score values. All models could reach high specificity (more than 96%) and high precision (80% or more) for predicting major outcomes. The models could also achieve a high sensitivity to predict minor outcomes. Finally, the accuracy of all models was about 75%. However, XGBoost and LGBM models achieved the best performance among all models. This study showcased the accuracy and reliability of machine learning models in the outcome prediction of methadone poisoning. [ABSTRACT FROM AUTHOR]
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- 2024
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13. Outcome prediction of methadone poisoning in the United States: implications of machine learning in the National Poison Data System (NPDS)
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Mehrpour, Omid, primary, Saeedi, Farhad, additional, Vohra, Varun, additional, and Hoyte, Christopher, additional
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- 2023
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14. Prevalence of Metabolic Syndrome and Its Associated Potential Factors among the Elderly in the East of Iran
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Farkhondeh, Tahereh, primary, Kazemi, Toba, additional, Bijari, Bita, additional, Sharifi, Farshad, additional, Moodi, Mitra, additional, Saeedi, Farhad, additional, Bizhaem, Saeede Khosravi, additional, Hoseinzadeh-Chahkandak, Fatemeh, additional, and Samarghandian, Saeed, additional
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- 2023
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15. The relationship between dietary patterns and insomnia in young women
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Karbasi, Samira, primary, Asadi, Zahra, additional, Mohaghegh, Zabihullah, additional, Saeedi, Farhad, additional, Ferns, Gordon A., additional, and Bahrami, Afsane, additional
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- 2023
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16. The role of decision tree and machine learning models for outcome prediction of bupropion exposure: A nationwide analysis of more than 14 000 patients in the United States
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Mehrpour, Omid, primary, Saeedi, Farhad, additional, Vohra, Varun, additional, Abdollahi, Jafar, additional, Shirazi, Farshad M., additional, and Goss, Foster, additional
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- 2023
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17. The value of machine learning for prognosis prediction of diphenhydramine exposure: National analysis of 50,000 patients in the United States
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Mehrpour, Omid, primary, Saeedi, Farhad, additional, Abdollahi, Jafar, additional, Amirabadizadeh, Alireza, additional, and Goss, Foster, additional
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- 2023
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18. Utility Of Support Vector Machine And Decision Tree To Identify The Prognosis Of Metformin Poisoning In The United States: Analysis Of National Poisoning Data System
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Mehrpour, Omid, primary, Saeedi, Farhad, additional, Hoyte, Christopher, additional, Goss, Foster, additional, and Shirazi, Farshad M, additional
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- 2022
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19. Curcumin and blood lipid levels: an updated systematic review and meta-analysis of randomised clinical trials.
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Saeedi, Farhad, Farkhondeh, Tahereh, Roshanravan, Babak, Amirabadizadeh, Alireza, Ashrafizadeh, Milad, and Samarghandian, Saeed
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BLOOD lipids , *CURCUMIN , *CLINICAL trials , *ANTILIPEMIC agents , *ODDS ratio , *LIPIDS - Abstract
The present study was designed to indicate the protective effects of curcumin on dyslipidemia. Main databases were searched to recognise randomised clinical trials evaluating the effect of curcumin on blood lipid profiles. The pooled odds ratio with a 95% confidence interval (CI) was used to evaluate the effect of curcumin on blood lipid parameters. HDL-C levels in the curcumin group were 0.04-fold lower than placebo (95% CI:−0.36–0.29; Z = 0.23; p =.82). LDL-C levels in the curcumin group reduced by 0.17 versus the placebo group (95% CI: −0.43–0.09; Z = 1.27; p =.2). TC levels in the curcumin group were 0.21 lower versus the placebo group (95% CI: −0.55–0.13; Z = 1.22; p =.22). TG level in the curcumin group were 0.05 lower versus the placebo (95% CI: −0.20–0.11; Z = 0.58; p =.56). This study suggests that curcumin may reduce blood lipid levels and can be used as a hypolipidemic agent. [ABSTRACT FROM AUTHOR]
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- 2022
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20. Prognostic factors of acetaminophen exposure in the United States: An analysis of 39,000 patients
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Mehrpour, Omid, primary, Saeedi, Farhad, additional, Hadianfar, Ali, additional, Mégarbane, Bruno, additional, and Hoyte, Christopher, additional
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- 2021
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21. Decision tree outcome prediction of acute acetaminophen exposure in the United States: A study of 30,000 cases from the National Poison Data System
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Mehrpour, Omid, primary, Saeedi, Farhad, additional, and Hoyte, Christopher, additional
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- 2021
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22. A systematic review of clinical and laboratory findings of lead poisoning: lessons from case reports
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Samarghandian, Saeed, primary, Shirazi, Farshad M., additional, Saeedi, Farhad, additional, Roshanravan, Babak, additional, Pourbagher-Shahri, Ali Mohammad, additional, Khorasani, Emad Yeganeh, additional, Farkhondeh, Tahereh, additional, Aaseth, Jan Olav, additional, Abdollahi, Mohammad, additional, and Mehrpour, Omid, additional
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- 2021
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23. Metabolic impact of saffron and crocin: an updated systematic and meta-analysis of randomised clinical trials.
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Roshanravan, Babak, Samarghandian, Saeed, Ashrafizadeh, Milad, Amirabadizadeh, Alireza, Saeedi, Farhad, and Farkhondeh, Tahereh
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CROCIN ,BLOOD lipids ,SAFFRON crocus ,CLINICAL trials ,BLOOD sugar - Abstract
The present systematic and meta-analysis study was designed to show the protective impact of saffron and crocin supplementation on hyperlipidaemia and hyperglycaemia in randomised and clinical trials (RCTs). A pooled analysis using a model for random-effects showed that HDL-C levels were 0.21 fold higher in the saffron and 0.01 fold higher in the crocin group than placebo. LDL-C levels in the saffron group reduced by 0.51 and 0.04 fold in the crocin group versus the placebo. Moreover, TC levels in the saffron group were 0.19 lower and 0.11 fold lower in crocin group than in the placebo group. TG level in saffron group was 0.04 lower and 0.02 fold lower in crocin than the control group. The blood glucose levels did not significantly differ from the control group. This study suggests that saffron and crocin may modulate the serum lipid profile in patient with metabolic disorders. [ABSTRACT FROM AUTHOR]
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- 2022
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24. Impact of Metformin on Cancer Biomarkers in Non-Diabetic Cancer Patients: A Systematic Review and Meta-Analysis of Clinical Trials
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Farkhondeh, Tahereh, primary, Amirabadizadeh, Alireza, additional, Aramjoo, Hamed, additional, Llorens, Silvia, additional, Roshanravan, Babak, additional, Saeedi, Farhad, additional, Talebi, Marjan, additional, Shakibaei, Mehdi, additional, and Samarghandian, Saeed, additional
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- 2021
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25. Evaluation of Diuretic and Antioxidant Properties in Aqueous Bark and Fruit Extracts of Pine
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Shariati, Hadi, primary, Hassanpour, Mohammad, additional, Sharifzadeh, Gholamreza, additional, Zarban, Asghar, additional, Samarghandian, Saeed, additional, and Saeedi, Farhad, additional
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- 2021
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26. Network-Based Analysis Reveals Association of FOXE1 Gene Polymorphisms in Thyroid Cancer Patients; A Case-Control Study in Southeast of Iran
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Mehrazin, Ahmad, primary, Safarpour, Hossein, additional, Davoudi, Seyedeh Tahmineh, additional, Parsamanesh, Negin, additional, Saeedi, Farhad, additional, and Miri-Moghaddam, Ebrahim, additional
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- 2020
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27. Curcumin and blood lipid levels: an updated systematic review and meta-analysis of randomised clinical trials
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Saeedi, Farhad, primary, Farkhondeh, Tahereh, additional, Roshanravan, Babak, additional, Amirabadizadeh, Alireza, additional, Ashrafizadeh, Milad, additional, and Samarghandian, Saeed, additional
- Published
- 2020
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28. Metabolic impact of saffron and crocin: an updated systematic and meta-analysis of randomised clinical trials
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Roshanravan, Babak, primary, Samarghandian, Saeed, additional, Ashrafizadeh, Milad, additional, Amirabadizadeh, Alireza, additional, Saeedi, Farhad, additional, and Farkhondeh, Tahereh, additional
- Published
- 2020
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29. Decision tree outcome prediction of acute acetaminophen exposure in the United States: A study of 30,000 cases from the National Poison Data System.
- Author
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Mehrpour, Omid, Saeedi, Farhad, and Hoyte, Christopher
- Subjects
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ACETAMINOPHEN , *DECISION trees , *POISONING , *POISONS , *LIVER function tests , *LIVER enzymes - Abstract
Acetaminophen is one of the most commonly used analgesic drugs in the United States. However, the outcomes of acute acetaminophen overdose might be very serious in some cases. Therefore, prediction of the outcomes of acute acetaminophen exposure is crucial. This study is a 6‐year retrospective cohort study using National Poison Data System (NPDS) data. A decision tree algorithm was used to determine the risk predictors of acetaminophen exposure. The decision tree model had an accuracy of 0.839, an accuracy of 0.836, a recall of 0.72, a specificity of 0.86 and an F1_score of 0.76 for the test group and an accuracy of 0.848, a recall of 0.85, a recall of 0.74, a specificity of 0.87 and an F1_score of 0.78 for the training group. Our results showed that elevated serum levels of liver enzymes, other liver function test abnormality, anorexia, acidosis, electrolyte abnormality, increased bilirubin, coagulopathy, abdominal pain, coma, increased anion gap, tachycardia and hypotension were the most important factors in determining the outcome of acute acetaminophen exposure. Therefore, the decision tree model is a reliable approach in determining the prognosis of acetaminophen exposure cases and can be used in an emergency room or during hospitalization. [ABSTRACT FROM AUTHOR]
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- 2022
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30. Developing Improvement Planning Phase in Project Management Maturity Models
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Eshtehardian, Ehsan, primary and Saeedi, Farhad, additional
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- 2016
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31. How Much Lucrative Drilling A Level 5 Multilateral Well Can Be In A Gas Condensate Reservoir From Offshore Platforms?
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Khosravani, Mohammad Javad, additional and Saeedi, Farhad, additional
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- 2008
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32. Population-level risks of alcohol consumption by amount, geography, age, sex, and year: a systematic analysis for the Global Burden of Disease Study 2020
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Dana Bryazka, Marissa B Reitsma, Max G Griswold, Kalkidan Hassen Abate, Cristiana Abbafati, Mohsen Abbasi-Kangevari, Zeinab Abbasi-Kangevari, Amir Abdoli, Mohammad Abdollahi, Abu Yousuf Md Abdullah, E S Abhilash, Eman Abu-Gharbieh, Juan Manuel Acuna, Giovanni Addolorato, Oladimeji M Adebayo, Victor Adekanmbi, Kishor Adhikari, Sangeet Adhikari, Qorinah Estiningtyas Sakilah Adnani, Saira Afzal, Wubetu Yimam Agegnehu, Manik Aggarwal, Bright Opoku Ahinkorah, Araz Ramazan Ahmad, Sajjad Ahmad, Tauseef Ahmad, Ali Ahmadi, Sepideh Ahmadi, Haroon Ahmed, Tarik Ahmed Rashid, Chisom Joyqueenet Akunna, Hanadi Al Hamad, Md Zakiul Alam, Dejene Tsegaye Alem, Kefyalew Addis Alene, Yousef Alimohamadi, Atiyeh Alizadeh, Kasim Allel, Jordi Alonso, Saba Alvand, Nelson Alvis-Guzman, Firehiwot Amare, Edward Kwabena Ameyaw, Sohrab Amiri, Robert Ancuceanu, Jason A Anderson, Catalina Liliana Andrei, Tudorel Andrei, Jalal Arabloo, Muhammad Arshad, Anton A Artamonov, Zahra Aryan, Malke Asaad, Mulusew A Asemahagn, Thomas Astell-Burt, Seyyed Shamsadin Athari, Desta Debalkie Atnafu, Prince Atorkey, Alok Atreya, Floriane Ausloos, Marcel Ausloos, Getinet Ayano, Martin Amogre ayanore Ayanore, Olatunde O Ayinde, Jose L Ayuso-Mateos, Sina Azadnajafabad, Melkalem Mamuye Azanaw, Mohammadreza Azangou-Khyavy, Amirhossein Azari Jafari, Ahmed Y Azzam, Ashish D Badiye, Nasser Bagheri, Sara Bagherieh, Mohan Bairwa, Shankar M Bakkannavar, Ravleen Kaur Bakshi, Awraris Hailu Balchut/Bilchut, Till Winfried Bärnighausen, Fabio Barra, Amadou Barrow, Pritish Baskaran, Luis Belo, Derrick A Bennett, Isabela M Benseñor, Akshaya Srikanth Bhagavathula, Neeraj Bhala, Ashish Bhalla, Nikha Bhardwaj, Pankaj Bhardwaj, Sonu Bhaskar, Krittika Bhattacharyya, Vijayalakshmi S Bhojaraja, Bagas Suryo Bintoro, Elena A Elena Blokhina, Belay Boda Abule Bodicha, Archith Boloor, Cristina Bosetti, Dejana Braithwaite, Hermann Brenner, Nikolay Ivanovich Briko, Andre R Brunoni, Zahid A Butt, Chao Cao, Yin Cao, Rosario Cárdenas, Andre F Carvalho, Márcia Carvalho, Joao Mauricio Castaldelli-Maia, Giulio Castelpietra, Luis F S Castro-de-Araujo, Maria Sofia Cattaruzza, Promit Ananyo Chakraborty, Jaykaran Charan, Vijay Kumar Chattu, Akhilanand Chaurasia, Nicolas Cherbuin, Dinh-Toi Chu, Nandita Chudal, Sheng-Chia Chung, Chuchu Churko, Liliana G Ciobanu, Massimo Cirillo, Rafael M Claro, Simona Costanzo, Richard G Cowden, Michael H Criqui, Natália Cruz-Martins, Garland T Culbreth, Berihun Assefa Dachew, Omid Dadras, Xiaochen Dai, Giovanni Damiani, Lalit Dandona, Rakhi Dandona, Beniam Darge Daniel, Anna Danielewicz, Jiregna Darega Gela, Kairat Davletov, Jacyra Azevedo Paiva de Araujo, Antonio Reis de Sá-Junior, Sisay Abebe Debela, Azizallah Dehghan, Andreas K Demetriades, Meseret Derbew Molla, Rupak Desai, Abebaw Alemayehu Desta, Diana Dias da Silva, Daniel Diaz, Lankamo Ena Digesa, Mengistie Diress, Milad Dodangeh, Deepa Dongarwar, Fariba Dorostkar, Haneil Larson Dsouza, Bereket Duko, Bruce B Duncan, Kristina Edvardsson, Michael Ekholuenetale, Frank J Elgar, Muhammed Elhadi, Mohamed A Elmonem, Aman Yesuf Endries, Sharareh Eskandarieh, Azin Etemadimanesh, Adeniyi Francis Fagbamigbe, Ildar Ravisovich Fakhradiyev, Fatemeh Farahmand, Carla Sofia e Sá Farinha, Andre Faro, Farshad Farzadfar, Ali Fatehizadeh, Nelsensius Klau Fauk, Valery L Feigin, Rachel Feldman, Xiaoqi Feng, Zinabu Fentaw, Simone Ferrero, Lorenzo Ferro Desideri, Irina Filip, Florian Fischer, Joel Msafiri Francis, Richard Charles Franklin, Peter Andras Gaal, Mohamed M Gad, Silvano Gallus, Fabio Galvano, Balasankar Ganesan, Tushar Garg, Mesfin Gebrehiwot Damtew Gebrehiwot, Teferi Gebru Gebremeskel, Mathewos Alemu Gebremichael, Tadele Regasa Gemechu, Lemma Getacher, Motuma Erena Getachew, Abera Getachew Obsa, Asmare Getie, Amir Ghaderi, Mansour Ghafourifard, Alireza Ghajar, Seyyed-Hadi Ghamari, Lilian A Ghandour, Mohammad Ghasemi Nour, Ahmad Ghashghaee, Sherief Ghozy, Franklin N Glozah, Ekaterina Vladimirovna Glushkova, Justyna Godos, Amit Goel, Salime Goharinezhad, Mahaveer Golechha, Pouya Goleij, Mohamad Golitaleb, Felix Greaves, Michal Grivna, Giuseppe Grosso, Temesgen Worku Gudayu, Bhawna Gupta, Rajeev Gupta, Sapna Gupta, Veer Bala Gupta, Vivek Kumar Gupta, Nima Hafezi-Nejad, Arvin Haj-Mirzaian, Brian J Hall, Rabih Halwani, Tiilahun Beyene Handiso, Graeme J Hankey, Sanam Hariri, Josep Maria Haro, Ahmed I Hasaballah, Hossein Hassanian-Moghaddam, Simon I Hay, Khezar Hayat, Golnaz Heidari, Mohammad Heidari, Delia Hendrie, Claudiu Herteliu, Demisu Zenbaba Heyi, Kamal Hezam, Mbuzeleni Mbuzeleni Hlongwa, Ramesh Holla, Md Mahbub Hossain, Sahadat Hossain, Seyed Kianoosh Hosseini, Mehdi hosseinzadeh, Mihaela Hostiuc, Sorin Hostiuc, Guoqing Hu, Junjie Huang, Salman Hussain, Segun Emmanuel Ibitoye, Irena M Ilic, Milena D Ilic, Mustapha Immurana, Lalu Muhammad Irham, M Mofizul Islam, Rakibul M Islam, Sheikh Mohammed Shariful Islam, Hiroyasu Iso, Ramaiah Itumalla, Masao Iwagami, Roxana Jabbarinejad, Louis Jacob, Mihajlo Jakovljevic, Zahra Jamalpoor, Elham Jamshidi, Sathish Kumar Jayapal, Umesh Umesh Jayarajah, Ranil Jayawardena, Rime Jebai, Seyed Ali Jeddi, Alelign Tasew Jema, Ravi Prakash Jha, Har Ashish Jindal, Jost B Jonas, Tamas Joo, Nitin Joseph, Farahnaz Joukar, Jacek Jerzy Jozwiak, Mikk Jürisson, Ali Kabir, Robel Hussen Kabthymer, Bhushan Dattatray Kamble, Himal Kandel, Girum Gebremeskel Kanno, Neeti Kapoor, Ibraheem M Karaye, Salah Eddin Karimi, Bekalu Getnet Kassa, Rimple Jeet Kaur, Gbenga A Kayode, Mohammad Keykhaei, Himanshu Khajuria, Rovshan Khalilov, Imteyaz A Khan, Moien AB Khan, Hanna Kim, Jihee Kim, Min Seo Kim, Ruth W Kimokoti, Mika Kivimäki, Vitalii Klymchuk, Ann Kristin Skrindo Knudsen, Ali-Asghar Kolahi, Vladimir Andreevich Korshunov, Ai Koyanagi, Kewal Krishan, Yuvaraj Krishnamoorthy, G Anil Kumar, Narinder Kumar, Nithin Kumar, Ben Lacey, Tea Lallukka, Savita Lasrado, Jerrald Lau, Sang-woong Lee, Wei-Chen Lee, Yo Han Lee, Lee-Ling Lim, Stephen S Lim, Stany W Lobo, Platon D Lopukhov, Stefan Lorkowski, Rafael Lozano, Giancarlo Lucchetti, Farzan Madadizadeh, Áurea M Madureira-Carvalho, Soleiman Mahjoub, Ata Mahmoodpoor, Rashidul Alam Mahumud, Alaa Makki, Mohammad-Reza Malekpour, Narayana Manjunatha, Borhan Mansouri, Mohammad Ali Mansournia, Jose Martinez-Raga, Francisco A Martinez-Villa, Richard Matzopoulos, Pallab K Maulik, Mahsa Mayeli, John J McGrath, Jitendra Kumar Meena, Entezar Mehrabi Nasab, Ritesh G Menezes, Gert B M Mensink, Alexios-Fotios A Mentis, Atte Meretoja, Bedasa Taye Merga, Tomislav Mestrovic, Junmei Miao Jonasson, Bartosz Miazgowski, Ana Carolina Micheletti Gomide Nogueira de Sá, Ted R Miller, GK Mini, Andreea Mirica, Antonio Mirijello, Seyyedmohammadsadeq Mirmoeeni, Erkin M Mirrakhimov, Sanjeev Misra, Babak Moazen, Maryam Mobarakabadi, Marcello Moccia, Yousef Mohammad, Esmaeil Mohammadi, Abdollah Mohammadian-Hafshejani, Teroj Abdulrahman Mohammed, Nagabhishek Moka, Ali H Mokdad, Sara Momtazmanesh, Yousef Moradi, Ebrahim Mostafavi, Sumaira Mubarik, Erin C Mullany, Beemnet Tekabe Mulugeta, Efrén Murillo-Zamora, Christopher J L Murray, Julius C Mwita, Mohsen Naghavi, Mukhammad David Naimzada, Vinay Nangia, Biswa Prakash Nayak, Ionut Negoi, Ruxandra Irina Negoi, Seyed Aria Nejadghaderi, Samata Nepal, Sudan Prasad Prasad Neupane, Sandhya Neupane Kandel, Yeshambel T Nigatu, Ali Nowroozi, Khan M Nuruzzaman, Chimezie Igwegbe Nzoputam, Kehinde O Obamiro, Felix Akpojene Ogbo, Ayodipupo Sikiru Oguntade, Hassan Okati-Aliabad, Babayemi Oluwaseun Olakunde, Gláucia Maria Moraes Oliveira, Ahmed Omar Bali, Emad Omer, Doris V Ortega-Altamirano, Adrian Otoiu, Stanislav S Otstavnov, Bilcha Oumer, Mahesh P A, Alicia Padron-Monedero, Raffaele Palladino, Adrian Pana, Songhomitra Panda-Jonas, Anamika Pandey, Ashok Pandey, Shahina Pardhan, Tarang Parekh, Eun-Kee Park, Charles D H Parry, Fatemeh Pashazadeh Kan, Jay Patel, Siddhartha Pati, George C Patton, Uttam Paudel, Shrikant Pawar, Amy E Peden, Ionela-Roxana Petcu, Michael R Phillips, Marina Pinheiro, Evgenii Plotnikov, Pranil Man Singh Pradhan, Akila Prashant, Jianchao Quan, Amir Radfar, Alireza Rafiei, Pankaja Raghav Raghav, Vafa Rahimi-Movaghar, Azizur Rahman, Md Mosfequr Rahman, Mosiur Rahman, Amir Masoud Rahmani, Shayan Rahmani, Chhabi Lal Ranabhat, Priyanga Ranasinghe, Chythra R Rao, Drona Prakash Rasali, Mohammad-Mahdi Rashidi, Zubair Ahmed Ratan, David Laith Rawaf, Salman Rawaf, Lal Rawal, Andre M N Renzaho, Negar Rezaei, Saeid Rezaei, Mohsen Rezaeian, Seyed Mohammad Riahi, Esperanza Romero-Rodríguez, Gregory A Roth, Godfrey M Rwegerera, Basema Saddik, Erfan Sadeghi, Reihaneh Sadeghian, Umar Saeed, Farhad Saeedi, Rajesh Sagar, Amirhossein Sahebkar, Harihar Sahoo, Mohammad Ali Sahraian, KM Saif-Ur-Rahman, Sarvenaz Salahi, Hamideh Salimzadeh, Abdallah M Samy, Francesco Sanmarchi, Milena M Santric-Milicevic, Yaser Sarikhani, Brijesh Sathian, Ganesh Kumar Saya, Mehdi Sayyah, Maria Inês Schmidt, Aletta Elisabeth Schutte, Michaël Schwarzinger, David C Schwebel, Abdul-Aziz Seidu, Nachimuthu Senthil Kumar, SeyedAhmad SeyedAlinaghi, Allen Seylani, Feng Sha, Sarvenaz Shahin, Fariba Shahraki-Sanavi, Shayan Shahrokhi, Masood Ali Shaikh, Elaheh Shaker, Murad Ziyaudinovich Shakhmardanov, Mehran Shams-Beyranvand, Sara Sheikhbahaei, Rahim Ali Sheikhi, Adithi Shetty, Jeevan K Shetty, Damtew Solomon Shiferaw, Mika Shigematsu, Rahman Shiri, Reza Shirkoohi, K M Shivakumar, Velizar Shivarov, Parnian Shobeiri, Roman Shrestha, Negussie Boti Sidemo, Inga Dora Sigfusdottir, Diego Augusto Santos Silva, Natacha Torres da Silva, Jasvinder A Singh, Surjit Singh, Valentin Yurievich Skryabin, Anna Aleksandrovna Skryabina, David A Sleet, Marco Solmi, YONATAN SOLOMON, Suhang Song, Yimeng Song, Reed J D Sorensen, Sergey Soshnikov, Ireneous N Soyiri, Dan J Stein, Sonu Hangma Subba, Miklós Szócska, Rafael Tabarés-Seisdedos, Takahiro Tabuchi, Majid Taheri, Ker-Kan Tan, Minale Tareke, Elvis Enowbeyang Tarkang, Gebremaryam Temesgen, Worku Animaw Temesgen, Mohamad-Hani Temsah, Kavumpurathu Raman Thankappan, Rekha Thapar, Nikhil Kenny Thomas, Chalachew Tiruneh, Jovana Todorovic, Marco Torrado, Mathilde Touvier, Marcos Roberto Tovani-Palone, Mai Thi Ngoc Tran, Sergi Trias-Llimós, Jaya Prasad Tripathy, Alireza Vakilian, Rohollah Valizadeh, Mehdi Varmaghani, Shoban Babu Varthya, Tommi Juhani Vasankari, Theo Vos, Birhanu Wagaye, Yasir Waheed, Mandaras Tariku Walde, Cong Wang, Yanzhong Wang, Yuan-Pang Wang, Ronny Westerman, Nuwan Darshana Wickramasinghe, Abate Dargie Wubetu, Suowen Xu, Kazumasa Yamagishi, Lin Yang, Gesila Endashaw E Yesera, Arzu Yigit, Vahit Yiğit, Ayenew Engida Ayenew Engida Yimaw, Dong Keon Yon, Naohiro Yonemoto, Chuanhua Yu, Siddhesh Zadey, Mazyar Zahir, Iman Zare, Mikhail Sergeevich Zastrozhin, Anasthasia Zastrozhina, Zhi-Jiang Zhang, Chenwen Zhong, Mohammad Zmaili, Yves Miel H Zuniga, Emmanuela Gakidou, University of St Andrews. School of Medicine, University of St Andrews. Population and Behavioural Science Division, Department of Public Health, University of Helsinki, Hjelt Institute (-2014), Helsinki Inequality Initiative (INEQ), Clinicum, Helsinki University Hospital Area, Bill & Melinda Gates Foundation, King Edward Medical University (Pakistán), Alexander von Humboldt Foundation, University of Oxford (Reino Unido), Medical Research Council (Reino Unido), NIH - National Institute of Mental Health (NIMH) (Estados Unidos), Canada Research Chairs, National Health and Medical Research Council (Australia), National Heart Foundation of Australia, Ministry of Education, Science and Technological Development (Serbia), Wellcome Trust, NIH - National Institute on Aging (NIA) (Estados Unidos), Finlands Akademi (Finlandia), Panjab University (India), Federal Ministry of Education & Research (Alemania), National Council for Scientific and Technological Development (Brasil), Danish National Research Foundation, Queensland Centre for Mental Health Research (Australia), South African Medical Research Council, National Natural Science Foundation of China, Charles Sturt University (Australia), Ain Shams University (Egipto), Mizoram University (India), Kasturba Medical College (India), Manipal Academy of Higher Education (India), Coordenação de Aperfeicoamento de Pessoal de Nível Superior (Brasil), Ministerio de Ciencia e Innovación (España), Collaborators, GBD 2020 Alcohol, Bryazka, Dana, Reitsma, Marissa B, Griswold, Max G, Abate, Kalkidan Hassen, Abbafati, Cristiana, Abbasi-Kangevari, Mohsen, Abbasi-Kangevari, Zeinab, Abdoli, Amir, Abdollahi, Mohammad, Abdullah, Abu Yousuf Md, Abhilash, E S, Abu-Gharbieh, Eman, Acuna, Juan Manuel, Addolorato, Giovanni, Adebayo, Oladimeji M, Adekanmbi, Victor, Adhikari, Kishor, Adhikari, Sangeet, Adnani, Qorinah Estiningtyas Sakilah, Afzal, Saira, Agegnehu, Wubetu Yimam, Aggarwal, Manik, Ahinkorah, Bright Opoku, Ahmad, Araz Ramazan, Ahmad, Sajjad, Ahmad, Tauseef, Ahmadi, Ali, Ahmadi, Sepideh, Ahmed, Haroon, Ahmed Rashid, Tarik, Akunna, Chisom Joyqueenet, Al Hamad, Hanadi, Alam, Md Zakiul, Alem, Dejene Tsegaye, Alene, Kefyalew Addi, Alimohamadi, Yousef, Alizadeh, Atiyeh, Allel, Kasim, Alonso, Jordi, Alvand, Saba, Alvis-Guzman, Nelson, Amare, Firehiwot, Ameyaw, Edward Kwabena, Amiri, Sohrab, Ancuceanu, Robert, Anderson, Jason A, Andrei, Catalina Liliana, Andrei, Tudorel, Arabloo, Jalal, Arshad, Muhammad, Artamonov, Anton A, Aryan, Zahra, Asaad, Malke, Asemahagn, Mulusew A, Astell-Burt, Thoma, Athari, Seyyed Shamsadin, Atnafu, Desta Debalkie, Atorkey, Prince, Atreya, Alok, Ausloos, Floriane, Ausloos, Marcel, Ayano, Getinet, Ayanore, Martin Amogre ayanore, Ayinde, Olatunde O, Ayuso-Mateos, Jose L, Azadnajafabad, Sina, Azanaw, Melkalem Mamuye, Azangou-Khyavy, Mohammadreza, Azari Jafari, Amirhossein, Azzam, Ahmed Y, Badiye, Ashish D, Bagheri, Nasser, Bagherieh, Sara, Bairwa, Mohan, Bakkannavar, Shankar M, Bakshi, Ravleen Kaur, Balchut/bilchut, Awraris Hailu, Bärnighausen, Till Winfried, Barra, Fabio, Barrow, Amadou, Baskaran, Pritish, Belo, Lui, Bennett, Derrick A, Benseñor, Isabela M, Bhagavathula, Akshaya Srikanth, Bhala, Neeraj, Bhalla, Ashish, Bhardwaj, Nikha, Bhardwaj, Pankaj, Bhaskar, Sonu, Bhattacharyya, Krittika, Bhojaraja, Vijayalakshmi S, Bintoro, Bagas Suryo, Blokhina, Elena A Elena, Bodicha, Belay Boda Abule, Boloor, Archith, Bosetti, Cristina, Braithwaite, Dejana, Brenner, Hermann, Briko, Nikolay Ivanovich, Brunoni, Andre R, Butt, Zahid A, Cao, Chao, Cao, Yin, Cárdenas, Rosario, Carvalho, Andre F, Carvalho, Márcia, Castaldelli-Maia, Joao Mauricio, Castelpietra, Giulio, Castro-de-Araujo, Luis F S, Cattaruzza, Maria Sofia, Chakraborty, Promit Ananyo, Charan, Jaykaran, Chattu, Vijay Kumar, Chaurasia, Akhilanand, Cherbuin, Nicola, Chu, Dinh-Toi, Chudal, Nandita, Chung, Sheng-Chia, Churko, Chuchu, Ciobanu, Liliana G, Cirillo, Massimo, Claro, Rafael M, Costanzo, Simona, Cowden, Richard G, Criqui, Michael H, Cruz-Martins, Natália, Culbreth, Garland T, Dachew, Berihun Assefa, Dadras, Omid, Dai, Xiaochen, Damiani, Giovanni, Dandona, Lalit, Dandona, Rakhi, Daniel, Beniam Darge, Danielewicz, Anna, Darega Gela, Jiregna, Davletov, Kairat, de Araujo, Jacyra Azevedo Paiva, de Sá-Junior, Antonio Rei, Debela, Sisay Abebe, Dehghan, Azizallah, Demetriades, Andreas K, Derbew Molla, Meseret, Desai, Rupak, Desta, Abebaw Alemayehu, Dias da Silva, Diana, Diaz, Daniel, Digesa, Lankamo Ena, Diress, Mengistie, Dodangeh, Milad, Dongarwar, Deepa, Dorostkar, Fariba, Dsouza, Haneil Larson, Duko, Bereket, Duncan, Bruce B, Edvardsson, Kristina, Ekholuenetale, Michael, Elgar, Frank J, Elhadi, Muhammed, Elmonem, Mohamed A, Endries, Aman Yesuf, Eskandarieh, Sharareh, Etemadimanesh, Azin, Fagbamigbe, Adeniyi Franci, Fakhradiyev, Ildar Ravisovich, Farahmand, Fatemeh, Farinha, Carla Sofia e Sá, Faro, Andre, Farzadfar, Farshad, Fatehizadeh, Ali, Fauk, Nelsensius Klau, Feigin, Valery L, Feldman, Rachel, Feng, Xiaoqi, Fentaw, Zinabu, Ferrero, Simone, Ferro Desideri, Lorenzo, Filip, Irina, Fischer, Florian, Francis, Joel Msafiri, Franklin, Richard Charle, Gaal, Peter Andra, Gad, Mohamed M, Gallus, Silvano, Galvano, Fabio, Ganesan, Balasankar, Garg, Tushar, Gebrehiwot, Mesfin Gebrehiwot Damtew, Gebremeskel, Teferi Gebru, Gebremichael, Mathewos Alemu, Gemechu, Tadele Regasa, Getacher, Lemma, Getachew, Motuma Erena, Getachew Obsa, Abera, Getie, Asmare, Ghaderi, Amir, Ghafourifard, Mansour, Ghajar, Alireza, Ghamari, Seyyed-Hadi, Ghandour, Lilian A, Ghasemi Nour, Mohammad, Ghashghaee, Ahmad, Ghozy, Sherief, Glozah, Franklin N, Glushkova, Ekaterina Vladimirovna, Godos, Justyna, Goel, Amit, Goharinezhad, Salime, Golechha, Mahaveer, Goleij, Pouya, Golitaleb, Mohamad, Greaves, Felix, Grivna, Michal, Grosso, Giuseppe, Gudayu, Temesgen Worku, Gupta, Bhawna, Gupta, Rajeev, Gupta, Sapna, Gupta, Veer Bala, Gupta, Vivek Kumar, Hafezi-Nejad, Nima, Haj-Mirzaian, Arvin, Hall, Brian J, Halwani, Rabih, Handiso, Tiilahun Beyene, Hankey, Graeme J, Hariri, Sanam, Haro, Josep 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Nk, Feigin, Vl, Feldman, R, Feng, Xq, Fentaw, Z, Ferrero, S, Desideri, Lf, Filip, I, Fischer, F, Francis, Jm, Franklin, Rc, Gaal, Pa, Gad, Mm, Gallus, S, Galvano, F, Ganesan, B, Garg, T, Gebrehiwot, Mgd, Gebremeskel, Tg, Gebremichael, Ma, Gemechu, Tr, Getacher, L, Getachew, Me, Obsa, Ag, Getie, A, Ghaderi, A, Ghafourifard, M, Ghajar, A, Ghamari, Sh, Ghandour, La, Nour, Mg, Ghashghaee, A, Ghozy, S, Glozah, Fn, Glushkova, Ev, Godos, J, Goel, A, Goharinezhad, S, Golechha, M, Goleij, P, Golitaleb, M, Greaves, F, Grivna, M, Grosso, G, Gudayu, Tw, Gupta, B, Gupta, R, Gupta, S, Gupta, Vb, Gupta, Vk, Nejad, Nh, Mirzaian, Ah, Hall, Bj, Halwani, R, Handiso, Tb, Hankey, Gj, Hariri, S, Haro, Jm, Hasaballah, Ai, Moghaddam, Hh, Hay, Si, Hayat, K, Heidari, G, Heidari, M, Hendrie, D, Herteliu, C, Heyi, Dz, Hezam, K, Hlongwa, Mm, Holla, R, Hossain, Mm, Hossain, S, Hosseini, Sk, Hosseinzadeh, M, Hostiuc, M, Hostiuc, S, Hu, Gq, Huang, Jj, Hussain, S, Ibitoye, Se, Ilic, Im, Ilic, Md, Immurana, M, Irham, 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Sigfusdottir, Id, Silva, Da, da Silva, Nt, Singh, Ja, Singh, S, Skryabin, Vy, Skryabina, Aa, Sleet, Da, Solmi, M, Solomon, Y, Song, S, Song, Ym, Sorensen, Rjd, Soshnikov, S, Soyiri, In, Stein, Dj, Subba, Sh, Szocska, M, Seisdedos, Rt, Tabuchi, T, Taheri, M, Tan, Kk, Tareke, M, Tarkang, Ee, Temesgen, G, Temesgen, Wa, Temsah, Mh, Thankappan, Kr, Thapar, R, Thomas, Nk, Tiruneh, C, Todorovic, J, Torrado, M, Touvier, M, Palone, Mrt, Tran, Mtn, Llimos, St, Tripathy, Jp, Vakilian, A, Valizadeh, R, Varmaghani, M, Varthya, Sb, Vasankari, Tj, Vos, T, Wagaye, B, Waheed, Y, Walde, Mt, Wang, C, Wang, Yz, Wang, Yp, Westerman, R, Wickramasinghe, Nd, Wubetu, Ad, Xu, S, Yamagishi, K, Yang, L, Yesera, Gee, Yigit, A, Yimaw, Ae, Yon, Dk, Yonemoto, N, Yu, Ch, Zadey, S, Zahir, M, Zare, I, Zastrozhin, M, Zastrozhina, A, Zhang, Zj, Zhong, Cw, Zmaili, M, Zuniga, Ymh, Gakidou, E, Madureira-Carvalho, Am, Ciobanu, LG, Gakidou, Emma, and GBD 2020 Alcohol Collaborators
- Subjects
Adult ,Male ,Alcohol Drinking ,CONTROL POLICIES ,adult ,Child, Preschool ,Female ,Geography ,Global Burden of Disease ,Global Health ,Humans ,Middle Aged ,Quality-Adjusted Life Years ,Risk Factors ,NDAS ,ALL-CAUSE ,GUIDELINES ,GBD 2020 Alcohol Collaborators ,COST-EFFECTIVENESS ,Medicine, General & Internal ,DRINKING ,SDG 3 - Good Health and Well-being ,RA0421 ,General & Internal Medicine ,Quality-Adjusted Life Year ,RA0421 Public health. Hygiene. Preventive Medicine ,DRINKERS ,Child ,Preschool ,11 Medical and Health Sciences ,METAANALYSIS ,MCC ,Science & Technology ,global burden of disease ,Risk Factor ,General Medicine ,CANCER ,alcohol drinking ,AC ,3121 General medicine, internal medicine and other clinical medicine ,REDUCED MORTALITY ,Life Sciences & Biomedicine ,Human - Abstract
Background: The health risks associated with moderate alcohol consumption continue to be debated. Small amounts of alcohol might lower the risk of some health outcomes but increase the risk of others, suggesting that the overall risk depends, in part, on background disease rates, which vary by region, age, sex, and year. Methods: For this analysis, we constructed burden-weighted dose-response relative risk curves across 22 health outcomes to estimate the theoretical minimum risk exposure level (TMREL) and non-drinker equivalence (NDE), the consumption level at which the health risk is equivalent to that of a non-drinker, using disease rates from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2020 for 21 regions, including 204 countries and territories, by 5-year age group, sex, and year for individuals aged 15-95 years and older from 1990 to 2020. Based on the NDE, we quantified the population consuming harmful amounts of alcohol. Findings: The burden-weighted relative risk curves for alcohol use varied by region and age. Among individuals aged 15-39 years in 2020, the TMREL varied between 0 (95% uncertainty interval 0-0) and 0·603 (0·400-1·00) standard drinks per day, and the NDE varied between 0·002 (0-0) and 1·75 (0·698-4·30) standard drinks per day. Among individuals aged 40 years and older, the burden-weighted relative risk curve was J-shaped for all regions, with a 2020 TMREL that ranged from 0·114 (0-0·403) to 1·87 (0·500-3·30) standard drinks per day and an NDE that ranged between 0·193 (0-0·900) and 6·94 (3·40-8·30) standard drinks per day. Among individuals consuming harmful amounts of alcohol in 2020, 59·1% (54·3-65·4) were aged 15-39 years and 76·9% (73·0-81·3) were male. Interpretation: There is strong evidence to support recommendations on alcohol consumption varying by age and location. Stronger interventions, particularly those tailored towards younger individuals, are needed to reduce the substantial global health loss attributable to alcohol. Research reported in this publication was supported by the Bill & Melinda Gates Foundation. S Afzal acknowledges the support for intellectual contributions to this manuscript by the Department of Community Medicine and Epidemiology at King Edward Medical University, Lahore, Pakistan. T Bärnighausen was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor award, funded by the German Federal Ministry of Education and Research. L Belo acknowledges support from FCT in the scope of the project UIDP/04378/2020 and UIDB/04378/2020 of UCIBIO and the project LA/P/0140/2020 of i4HB. D Bennett is supported by the UK Medical Research Council Population Health Research Unit at the University of Oxford (Oxford, UK). M Carvalho acknowledges support from FCT in the scope of the project UIDP/04378/2020 and UIDB/04378/2020 of UCIBIO and the project LA/P/0140/2020 of i4HB. L Castro-de-Araujo was funded by the Medical Research Council (UK), Grant no. MR/T03355X/1 and by the National Institute of Mental Health Grant no. R01MH128911. FJ Elgar is supported by the Canada Research Chairs program. F Greaves acknowledges support from the NIHR Applied Research Collaboration for NW London. V K Gupta acknowledges funding support from the National Health and Medical Research Council (NHMRC), Australia. VB Gupta acknowledges funding support from the National Health and Medical Research Council (NHMRC), Australia. C Herteliu is partially supported by a grant from the Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, project number PN-III-P4-ID-PCCF-2016-0084. C Herteliu is partially supported by a grant from the Romanian Ministry of Research Innovation and Digitalization, MCID, project number ID-585-CTR-42-PFE-2021. S Hussain was supported by the Operational Programme Research, Development and Education –Project, Postdoc2MUNI “(No. CZ.02.2.69/0.0/0.0/18_053/0016952). S M S Islam is funded by the National Health and Medical Research Council and received funding from the National Heart Foundation of Australia. The Serbian part of this GBD-related contribution has been co-financed through Grant OI 175 014 of the Ministry of Education Science and Technological Development of the Republic of Serbia. M Kivimaki was supported by the Wellcome Trust (221854/Z/20/Z), the UK Medical Research Council (MR/S011676/1), the US National Institute on Aging (R01AG056477), and the Academy of Finland (350426). K Krishan is supported by the UGC Centre of Advanced Study (Phase II), awarded to the Department of Anthropology, Panjab University, Chandigarh, India. B Lacey acknowledges support from the UK Biobank, funded largely by the UK Medical Research Council and Wellcome. S Lorkowski acknowledges institutional support from the Competence Cluster for Nutrition and Cardiovascular Health (nutriCARD) Halle-Jena-Leipzig (Germany; German Federal Ministry of Education and Research; grant agreement number 01EA1808A). G Lucchetti received a productivity scholarship from the Brazilian National Council for Scientific and Technological Development — CNPq (Level 1D). J McGrath was supported by the Danish National Research Foundation (Niels Bohr Professor). J McGrath is employed by the Queensland Centre for Mental Health Research (Australia), which receives support from the Queensland Health Department. C Parry acknowleges the South African Medical Research Council. A Peden is supported by a National Health and Medical Research Council Emerging Leadership Fellowship (Grant ID: APP2009306). M R Phillips was supported in part by the Global Alliance for Chronic Diseases - National Natural Science Foundation of China (NSFC. No. 81761128031). M Pinheiro acknowledges FCT for funding through program DL 57/2016 – Norma transitória. A Rahman acknowledges the support from the Data Science Research Unit in Charles Sturt University (Bathurst, NSW, Australia). U Saeed would like to acknowledge the International Center of Medical Sciences Research (ICMSR), Islamabad, Pakistan. A M Samy acknowledges support from Ain Shams University (Cairo, Egypt) and the Egyptian Fulbright Mission Program. N Senthil Kumar acknowledges the DBT, New Delhi sponsored Advanced State Level Biotech Hub (BT/NER/143/SP44475/2021), Mizoram University (Aizawl, Mizoram, India) for facilitating this work. F Sha is supported by the Shenzhen Science and Technology Program (Grant No. KQTD20190929172835662). A Shetty acknowledges Kasturba Medical College (Mangalore, India) and Manipal Academy of Higher Education (Manipal, India) for all the academic support. R Shrestha acknowledges a career development award from the National Institutes of Health (K01DA051346). D Silva was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior-Brazil (CAPES)-Finance Code 001 and is supported in part by CNPq - Brazil (309589/2021-5). D Sleet acknowledges partial support from Veritas Management Group, Inc and The Bizzell Group, LLC. S Trias-Llimós acknowledges research funding from the Juan de la Cierva-Formación program of the Spanish Ministry of Science and Innovation (FJC-2019-039314-I). Sí
- Published
- 2022
33. Prevalence of Metabolic Syndrome and Its Associated Potential Factors among the Elderly in the East of Iran.
- Author
-
Kazemi T, Bijari B, Sharifi F, Moodi M, Saeedi F, Bizhaem SK, Hoseinzadeh-Chahkandak F, Samarghandian S, and Farkhondeh T
- Subjects
- Male, Humans, Female, Aged, Middle Aged, Overweight, Prevalence, Cross-Sectional Studies, Iran epidemiology, Obesity epidemiology, Lipids, Risk Factors, Metabolic Syndrome
- Abstract
Background and Aims: This cross-sectional study aimed to determine potential factors with a strong association with metabolic syndrome (MetS) among obesity and lipid-related parameters, and liver enzymes, fasting blood glucose (FBG), and blood pressure (BP) as well as some sociodemographic factors in elderly over 60 years old from a sample of Birjand Longitudinal Aging Study (BLAS)., Methods: A total of 1366 elderly Birjand participants were enrolled and divided into non-MetS (n = 512) and MetS (n = 854) groups based on the status of MetS from January 2018 to October 2018. The anthropometric parameters, blood lipid profiles, liver enzymes, and disease history were evaluated and recorded., Results: 62.5% of the participants from our sample of elderly Birjand have MetS (33.4% in males and 66.6% in females). The prevalence of MetS in females was significantly higher than in males (P < 0.001). The increasing trend in the number of MetS components (from 0 to 5) was observed in females (p < 0.001). Odds ratio showed a strong association between female gender [8.33 (5.88- 11.82)], obesity [8.00 (4.87-13.14)], and overweight [2.44 (1.76-3.40)] with MetS and acceptable association between TG/HDL [(1.85 (1.62-2.12)] with MetS., Conclusion: This study indicated that the female sex, overweight and obesity have a strong association with MetS and TG/HDL has an acceptable association found in the sample of the elderly Birjand population. However, due to the obvious limitations of our study including the homogeneous sex and race of population, and no adjustment for several important confounding factors including sex, different ages, stage in the elderly, alcohol consumption, smoking, married status, physical activity, diet, and family history of CVD, more epidemiological investigations are needed to address this question., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)
- Published
- 2023
- Full Text
- View/download PDF
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